Achievements, Global Perspective
Our solutions have been successfully deployed in multiple universities across China and abroad, achieving excellent results. This demonstrates both the advancement of our technology and the reliability of our solutions. We look forward to sharing this proven experience with you and creating the first benchmark project together.
Home / Lab

Solution based case study

Integrating large language and visual model technologies, it supports multi-sensor collaboration and can be applied in scenarios such as intelligent interaction, task execution, experimental training, and knowledge learning. It helps students progress from theoretical understanding to practical application, develop core AI competencies, and align with the demands of future industries.

It supports voice commands that directly control robot movements. Through human-computer interaction, students gain a deeper understanding of AI principles, making programming and interaction more closely aligned with real-world applications.

Dual cameras integrated with visual large-model algorithms enable object recognition, scene analysis, and autonomous decision-making, providing high-precision visual support for interdisciplinary projects.

Individual Flight Competition:
Participants control their drones within a designated area, taking off from and landing at the starting zone. The task is to complete the designated individual flight course, during which points are awarded or deducted based on performance. The participant with the highest total score ranks higher; if scores are tied, the one with the shorter flight time wins. Each participant flies twice, and the best score is recorded.

Team Relay Flight Competition:
Teams of four participants operate drones manually within a defined area. Following the prescribed sequence and course, they must complete the flight in a relay format, passing through all obstacles as required. Except for takeoff and landing, the course must be completed twice — two participants per lap. Rankings are determined by the team’s total score and completion time; in the event of a tie, the team with the shorter total time wins.

Assembly and Logistics Transport Competition:
Participants must assemble and debug their equipment within a set time limit, then control their drone to complete a materials transport task according to competition rules. Rankings are based on the total score from assembly, debugging, and flight performance, as well as flight time. If total scores are tied, the participant with the shorter flight time wins.

10000+

Serve over schools nationwide

500000+

Accumulated students served

1000+

Collaborative Partners